This study was designed to assess non-medical prescription opioid use among a sample of opioid dependent participants.

Methods

A cross-sectional survey was conducted with a convenience sample of patients hospitalized for medical management of opioid withdrawal. We collected data related to participant demographics, socio-economic characteristics, the age of first opioid use, types of opioids preferred, and routes of administration. We also asked participants to describe how they first began using opioids and how their use progressed over time.

Results

Among the 75 participants, the mean age was 32 years (SD: ± 11, range: 18-70), 49 (65%) were men, 58 (77%) considered themselves to be “white,” 55 (74%) had a high school diploma or equivalent, and 39 (52%) were unemployed. All of these participants considered themselves to be “addicted.” Thirty-one (41%) felt that their addiction began with “legitimate prescriptions,” 24 (32%) with diverted prescription medications, and 20 (27%) with “street drugs” from illicit sources; however, 69 (92%) had reported purchasing opioids “off the street” at some point in time. Thirty-seven (49%) considered heroin to be their current preferred drug, and 43 (57%) had used drugs intravenously.

Conclusions

We found that many treatment-seeking opioid dependent patients first began using licit prescription drugs before obtaining opioids from illicit sources. Later, they purchased heroin, which they would come to prefer because it was less expensive and more effective than prescription drugs.

A mechanism-based model was developed to describe the time course of arthritis progression in the rat. Arthritis was induced in male Lewis rats with type II porcine collagen into the base of the tail. Disease progression was monitored by paw swelling, bone mineral density (BMD), body weights, plasma corticosterone (CST) concentrations, and TNF-α, IL-1β, IL-6, and glucocorticoid receptor (GR) mRNA expression in paw tissue. Bone mineral density was determined by PIXImus II dual energy x-ray densitometry. Plasma CST was assayed by HPLC. Cytokine and GR mRNA were determined by quantitative real-time polymerase chain reaction. Disease progression models were constructed from transduction and indirect response models and applied using S-ADAPT software. A delay in the onset of increased paw TNF-α and IL-6 mRNA concentrations was successfully characterized by simple transduction. This rise was closely followed by an up-regulation of GR mRNA and CST concentrations. Paw swelling and body weight responses peaked approximately 21 days post induction while bone mineral density changes were greatest at 23 days post induction. After peak response the time course in IL-1β, IL-6 mRNA, and paw edema slowly declined towards a disease steady-state. Model parameters indicate TNF-α and IL-1β mRNA most significantly induce paw edema while IL-6 mRNA exerted the most influence on BMD. The model for bone mineral density captures rates of turnover of cancellous and cortical bone and the fraction of each in the different regions analyzed. This small systems model integrates and quantitates multiple factors contributing to arthritis in rats.